Performance Regression or Improvement: pytorch_image_classification_benchmarks-resnet152-mean_inference_batch_latency_micro_secs:mean_inference_batch_latency_micro_secs

[github-actions]

Performance change found in the
test: pytorch_image_classification_benchmarks-resnet152-mean_inference_batch_latency_micro_secs for the metric: mean_inference_batch_latency_micro_secs.

For more information on how to triage the alerts, please look at
Triage performance alert issues section of the README.

Test description: Pytorch image classification on 50k images of size 224 x 224 with resnet 152.
Test link -

beam/.test-infra/jenkins/job_InferenceBenchmarkTests_Python.groovy

Line 63 in 42d0a6e

test : 'apache_beam.testing.benchmarks.inference.pytorch_image_classification_benchmarks',

Test dashboard - http://metrics.beam.apache.org/d/ZpS8Uf44z/python-ml-runinference-benchmarks?orgId=1&viewPanel=2

timestamp: Sat Oct 26 04:56:07 2024, metric_value: 8116539.03
timestamp: Fri Oct 25 05:06:41 2024, metric_value: 8051141.77
timestamp: Thu Oct 24 04:56:38 2024, metric_value: 7857721.34 <---- Anomaly
timestamp: Wed Oct 23 04:52:21 2024, metric_value: 6743111.68
timestamp: Tue Oct 22 04:58:28 2024, metric_value: 6942466.21
timestamp: Mon Oct 21 04:53:27 2024, metric_value: 6684983.30
timestamp: Sun Oct 20 04:53:07 2024, metric_value: 6664917.29
timestamp: Sat Oct 19 04:55:22 2024, metric_value: 6519499.33
timestamp: Fri Oct 18 04:54:46 2024, metric_value: 6742087.50
timestamp: Thu Oct 17 04:59:09 2024, metric_value: 6710194.12
timestamp: Wed Oct 16 04:57:32 2024, metric_value: 6690769.70
timestamp: Tue Oct 15 04:53:15 2024, metric_value: 6930970.29
timestamp: Mon Oct 14 04:51:47 2024, metric_value: 6699443.27

[liferoad]

http://35.193.202.176/d/ZpS8Uf44z/python-ml-runinference-benchmarks?orgId=1&viewPanel=2